---
title: "CP Survey Data Summary"
date: '`r format(Sys.Date(), format="%B %d, %Y")`'
output:
  flexdashboard::flex_dashboard:
    navbar:
      - { title: "by Joyce Lee", href: "https://www.joyceylee.com", align: left }
    theme: cerulean
    vertical_layout: fill
    orientation: rows
    social: [ "twitter", "menu" ]
    source_code: embed 
---

```{r setup}
load("~/Box Sync/University of Michigan /Winter 2018/Coding_Dataviz/Week 7/Week7.RData")
library(knitr)
library(flexdashboard)
library(leaflet)
library(DT)
library(formattable)
library(rpivotTable)
library(ggplot2)
library(ggthemes)
library(plotly)
library(dplyr)
library(leaflet)
library(pander)
```

```{r colors}
mycolors<-c("red", "orange", "yellow", "green", "purple")
```

Interactive DataViz 
=======================================

Row
---------------------------------------

###Quick overview of corporal punishment survey results

```{r}

valueBox(paste("Dashboards"), 
         color="success")
```

###Data from corporal punishment survey with 70 non-white participants 

```{r}

valueBox(paste("Data Source"),
         color="warning")
```

###Participants 

```{r}

valueBox(length(cpdata$ResponseId),
         icon="ion-ios-people")
```

###Average Age (Years)
```{r}
valueBox("32",
         icon="ion-ios-personadd")
```

Row
---------------------------------------

###Ethnicity and Race 

```{r}
r<- cpdata %>% 
  group_by(Q35) %>% 
  summarize(count=n()) %>% 
  plot_ly(x=~Q35, 
          y=~count,
          color=I("dark blue"),
          type="bar") %>% 
  layout(xaxis=list(title="Ethnicity or Race"),
         yaxis=list(title="Count"))
r  
```

### Gender 

```{r, fig.width=3, fig.height=5}
g<-cpdata %>% 
  group_by(Q34) %>% 
  summarize(count=n()) %>% 
  plot_ly(labels=~Q34, 
          values=~count,
          marker=list(colors=c("light blue", "gold"))) %>% 
  add_pie(hole=0.4) 
g

```

### Relationship Status

```{r, fig.width=3, fig.height=5}
r<-cpdata %>% 
  group_by(Q37) %>% 
  summarize(count=n()) %>% 
  plot_ly(labels=~Q37, 
          values=~count,
          marker=list(colors=c("pink", "grey", "magenta", "purple"))) %>% 
  add_pie(hole=0.4) 
r
```

Row
---------------------------------------

### Education 
```{r, fig.width=4}
e <- cpdata %>% 
  group_by(Q36) %>%
  summarise(percent=n()) %>% 
  mutate(percent=percent/sum(percent)*100) %>% 
  plot_ly(x=~percent, 
          y=~Q36,
          marker=list(color=mycolors),
          type="bar") %>% 
  layout(xaxis=list(title="Percentage"),
         yaxis=list(title="Education Level", showticklabels=FALSE)) 
  

e
```

### Income 

```{r, fig.width=4, fig.height=5}
i<-cpdata %>% 
  group_by(Q41) %>% 
  summarize(count=n()) %>% 
  plot_ly(labels=~Q41, 
          values=~count,
          marker=list(colors="Set1")) %>% 
  add_pie(hole=0.4) 
i
```

### Corporal Punishment MTurk Participants by Geography

```{r}
m<-leaflet(data=cpdata,
           height = 500,
           width = 1000)  %>% 
  setView(lng = mean(cpdata$LocationLongitude), 
          lat = mean(cpdata$LocationLatitude), zoom=3) %>% 
  addProviderTiles("Stamen.TonerLite", group = "Toner Lite")

m %>% addMarkers(lng = ~LocationLongitude, 
                       lat = ~LocationLatitude,
                       popup = ~as.character(location))

```